This thesis aims to study and analyse the complex spatio-social relations among social entities who interact together in a spatially structured social group. This aim is approached in three steps: 1. Collecting and classifying spatio-social data, 2. Disambiguating place names that people use to refer to their homes and 3. Analysis of data of this kind (numerical and visual). The source of spatio-social data used in this work is Flickr. Flickr is a yahoo photo sharing site. Users have a social network of friends and a collection of photos on their profiles. According to available statistics1 the Flickr database contains more than three billion photos, out of which a hundred million are geo-tagged. In retrieving data from Flickr database two different samples have been explored. Initially a random collection of photos that have been uploaded in Flickr during the examined periods has been collected on a daily basis. This is followed by much narrower and more precise criteria for the second data sampling that resulted in Flickr sample GB data. The thesis concludes that location dominates a significant pattern in online behavior of social entities who interact together via internet. The core contributions of this thesis are in the areas of: 1. Extracting indicative sample from very large data sets, 2. Disambiguation of place names that people use in their natural language to refer to their home locations and 3. Proposing potential new insights into behaviors of social entities with spatio-social relations. Overall, the popularity of social networking sites and availability of data that can be obtained from the web (whether people provide voluntarily or can be retrieve as a consequence of online interactions) are likely to continue the increasing trend in future. In addition, the realm of spatio-social data analysis and its visualization also continue to expand, as do the types of maps that are achievable, the visualization packages that the maps can be built with, the number of map users and improved gazetteers with more comprehensive coverage of vague terms. Therefore, the developed methods, algorithm and applications in this study can be beneficial to researchers in social and e-social sciences, those who are interested in developing and maintaining social networking sites, geographers who work on disambiguation of fuzzy vernacular geographic terms, visualization and spatial data analysts in general and those who are looking for development and accommodation of better business strategies (i.e. localization and personalization). 1 (http://www.Flickr.com, retrieved 20/07/09)